Browsing by Author "Galar, Diego"
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Item Adaptation of a Branching Algorithm to Solve the Multi-Objective Hamiltonian Cycle Problem(Springer, Cham, 2020) Murua, Maialen; Galar, Diego; Santana, RobertoThe Hamiltonian cycle problem (HCP) consists of finding a cycle of length N in an N-vertices graph. In this investigation, a graph G is considered with an associated set of matrices, in which each cell in the matrix corresponds to the weight of an arc. Thus, a multi-objective variant of the HCP is addressed and a Pareto set of solutions that minimizes the weights of the arcs for each objective is computed. To solve the HCP problem, the Branch-and-Fix algorithm is employed, a specific branching algorithm that uses the embedding of the problem in a particular stochastic process. To address the multi-objective HCP, the Branch-and-Fix algorithm is extended by computing different Hamiltonian cycles and fathoming the branches of the tree at earlier stages. The introduced anytime algorithm can produce a valid solution at any time of the execution, improving the quality of the Pareto Set as time increases.Item Condition monitoring of wind turbine pitch controller: A maintenance approach: A maintenance approach(2018-07) González-González, Asier; Jimenez Cortadi, Alberto; Galar, Diego; Ciani, Lorenzo; Tecnalia Research & Innovation; IAWith the increase of wind power capacity worldwide, researchers are focusing their attention on the operation and maintenance of wind turbines. A proper pitch controller must be designed to extend the life cycle of a wind turbine’s blades and tower. The pitch control system has two primaries, but conflicting, objectives: to maximize the wind energy captured and converted into electrical energy and to minimize fatigue and mechanical load. Four metrics have been proposed to balance these two objectives. Also, diverse pitch controller strategies are proposed in this paper to evaluate these objectives. This paper proposes a novel metrics approach to achieve the conflicting objectives with a maintenance focus. It uses a 100 kW wind turbine as a case study to simulate the proposed pitch control strategies and evaluate with the metrics proposed. The results are shown in two tables due to two different wind models are used.Item Condition-Based Maintenance of HVAC on a High-Speed Train for Fault Detection(2021-06-12) Ciani, Lorenzo; Guidi, Giulia; Patrizi, Gabriele; Galar, Diego; Tecnalia Research & InnovationReliability-centered maintenance (RCM) is a well-established method for preventive maintenance planning. This paper focuses on the optimization of a maintenance plan for an HVAC (heating, ventilation and air conditioning) system located on high-speed trains. The first steps of the RCM procedure help in identifying the most critical items of the system in terms of safety and availability by means of a failure modes and effects analysis. Then, RMC proposes the optimal maintenance tasks for each item making up the system. However, the decision-making diagram that leads to the maintenance choice is extremely generic, with a consequent high subjectivity in the task selection. This paper proposes a new fuzzy-based decision-making diagram to minimize the subjectivity of the task choice and preserve the cost-efficiency of the procedure. It uses a case from the railway industry to illustrate the suggested approach, but the procedure could be easily applied to different industrial and technological fields. The results of the proposed fuzzy approach highlight the importance of an accurate diagnostics (with an overall 86% of the task as diagnostic-based maintenance) and condition monitoring strategy (covering 54% of the tasks) to optimize the maintenance plan and to minimize the system availability. The findings show that the framework strongly mitigates the issues related to the classical RCM procedure, notably the high subjectivity of experts. It lays the groundwork for a general fuzzy-based reliability-centered maintenance method.Item Ergonomics Evaluation in Designed Maintainability: Case Study Using 3 DSSPP: Case Study Using 3 DSSPP(2021-12-01) Teymourian, Kiumars; Tretten, Phillip; Seneviratne, Dammika; Galar, Diego; Tecnalia Research & Innovation; INDUSTRY_THINGSMaintainability is one of the design parameters (reliability, availability, maintainability, and safety (RAMS)) and maintenance is needed to keep the respective design in sustainable use. At the same time, the human is involved in the form of interface and interaction in an engineered product/system designed. Ergonomics is a multi-discipli nary science that considers human capabilities and limitations in a broader sense. The objective of this paper is to integrate ergonomics into the maintainability design process in order to facilitate maintenance operation in lesser; time, cost, easier operation as well as the well-being of human who is involved. In other words, good er gonomics lead to good economics and in a broader sense, sustainability. This investigation shows that designing comfortable workplaces and lesser workload for maintenance operators will be beneficial for the maintainability design process and also improve the meantime to repair MTTR. In order to evaluate the effect of designed work place and workload on maintainers 3 D Static Strength Prediction Program (3D SSPP) that is commonly used as an ergonomics evaluation tool in scientific studies was applied.Item Fault Detection and RUL Estimation for Railway HVAC Systems Using a Hybrid Model-Based Approach(2021-06-16) Gálvez, Antonio; Diez-Olivan, Alberto; Seneviratne, Dammika; Galar, Diego; Tecnalia Research & Innovation; INDUSTRY_THINGSHeating, ventilation, and air conditioning (HVAC) systems installed in a passenger train carriage are critical systems, whose failures can affect people or the environment. This, together with restrictive regulations, results in the replacement of critical components in initial stages of degradation, as well as a lack of data on advanced stages of degradation. This paper proposes a hybrid model-based approach (HyMA) to overcome the lack of failure data on a HVAC system installed in a passenger train carriage. The proposed HyMA combines physics-based models with data-driven models to deploy diagnostic and prognostic processes for a complex and critical system. The physics-based model generates data on healthy and faulty working conditions; the faults are generated in different levels of degradation and can appear individually or together. A fusion of synthetic data and measured data is used to train, validate, and test the proposed hybrid model (HyM) for fault detection and diagnostics (FDD) of the HVAC system. The model obtains an accuracy of 92.60%. In addition, the physics-based model generates run-to-failure data for the HVAC air filter to develop a remaining useful life (RUL) prediction model, the RUL estimations performed obtained an accuracy in the range of 95.21–97.80% Both models obtain a remarkable accuracy. The development presented will result in a tool which provides relevant information on the health state of the HVAC system, extends its useful life, reduces its life cycle cost, and improves its reliability and availability; thus enhancing the sustainability of the system.Item FMECA Assessment for Railway Safety-Critical Systems Investigating a New Risk Threshold Method(2021) Catelani, Marcantonio; Ciani, Lorenzo; Galar, Diego; Guidi, Giulia; Matucci, Serena; Patrizi, Gabriele; Tecnalia Research & InnovationThis paper develops a Failure Mode, Effects and Criticality Analysis (FMECA) for a heating, ventilation and air conditioning (HVAC) system in railway. HVAC is a safety critical system which must ensure emergency ventilation in case of fire and in case of loss of primary ventilation functions. A study of the HVAC’s critical areas is mandatory to optimize its reliability and availability and consequently to guarantee a low operation and maintenance cost. The first part of the paper describes the FMECA which is performed and reported to highlight the main criticalities of the HVAC system under analysis. Secondly, the paper deals with the problem of the evaluation of a threshold risk value, which can distinguish negligible and critical failure modes. Literature barely considers the problem of an objective risk threshold estimation. Therefore, a new analytical method based on finite difference is introduced to find a univocal risk threshold value. The method is then tested on two Risk Priority Number datasets related to the same HVAC. The threshold obtained in both cases is a good tradeoff between the risk mitigation and the cost investment for the corrective actions required to mitigate the risk level. Finally, the threshold obtained with the proposed method is compared with the methods available in literature. The comparison shows that the proposed finite difference method is a well-structured technique, with a low computational cost. Furthermore, the proposed approach provides results in line with the literature, but it completely deletes the problem of subjectivity.Item Risk Assessment of a Wind Turbine: A New FMECA-Based Tool With RPN Threshold Estimation: A New FMECA-Based tool with RPN threshold estimation(2020) Catelani, Marcantonio; Ciani, Lorenzo; Galar, Diego; Patrizi, Gabriele; Tecnalia Research & InnovationA wind turbine is a complex system used to convert the kinetic energy of the wind into electrical energy. During the turbine design phase, a risk assessment is mandatory to reduce the machine downtime and the Operation & Maintenance cost and to ensure service continuity. This paper proposes a procedure based on Failure Modes, Effects, and Criticality Analysis to take into account every possible criticality that could lead to a turbine shutdown. Currently, a standard procedure to be applied for evaluation of the risk priority number threshold is still not available. Trying to fill this need, this paper proposes a new approach for the Risk Priority Number (RPN) prioritization based on a statistical analysis and compares the proposed method with the only three quantitative prioritization techniques found in literature. The proposed procedure was applied to the electrical and electronic components included in a Spanish 2 MW on-shore wind turbine.Item Smart maintenance and inspection of linear assets: An Industry 4.0 approach: An Industry 4.0 approach(2018) Seneviratne, Dammika; Ciani, Lorenzo; Catelani, Marcantonio; Galar, Diego; Tecnalia Research & Innovation; INDUSTRY_THINGSLinear assets have linear properties, for instance, similar underlying geometry and characteristics, over a distance. They show specific patterns of continuous inherent deteriorations and failures. Therefore, remedial inspection and maintenance actions will be similar along the length of a linear asset, but because as the asset is distributed over a large area, the execution costs are greater. Autonomous robots, for instance, unmanned aerial vehicles, pipe inspection gauges, and remotely operated vehicles, are used in different industrial settings in an ad-hoc manner for inspection and maintenance. Autonomous robots can be programmed for repetitive and specific tasks; this is useful for the inspection and maintenance of linear assets. This paper reviews the challenges of maintaining the linear assets, focusing on inspections. It also provides a conceptual framework for the use of autonomous inspection and maintenance practices for linear assets to reduce maintenance costs, human involvement, etc., whilst improving the availability of linear assets by effective use of autonomous robots and data from different sources.Item A statistical data-based approach to instability detection and wear prediction in radial turning processes(2018) Jimenez Cortadi, Alberto; Irigoien, Itziar; Boto, Fernando; Sierra, Basilio; Suarez, Alfredo; Galar, Diego; Tecnalia Research & Innovation; FACTORY; FABRIC_INTELRadial turning forces for tool-life improvements are studied, with the emphasis on predictive rather than preventive maintenance. A tool for wear prediction in various experimental settings of instability is proposed through the application of two statistical approaches to process data on tool-wear during turning processes: three sigma edit rule analysis and Principal Component Analysis (PCA). A Linear Mixed Model (LMM) is applied for wear prediction. These statistical approaches to instability detection generate results of acceptable accuracy for delivering expert opinion. They may be used for on-line monitoring to improve the processing of different materials. The LMM predicted significant differences for tool wear when turning different alloys and with different lubrication systems. It also predicted the degree to which the turning process could be extended while conserving stability. Finally, it should be mentioned that tool force in contact with the material was not considered to be an important input variable for the model.Item Tool-Path Problem in Direct Energy Deposition Metal-Additive Manufacturing: Sequence Strategy Generation(IEEE, 2020-05) Murua, Maialen; Suarez, Alfredo; Galar, Diego; Santana, RobertoThe tool-path problem has been extensively studied in manufacturing technologies, as it has a considerable impact on production time. Additive manufacturing is one of these technologies; it takes time to fabricate parts, so the selection of optimal tool-paths is critical. This research analyzes the tool-path problem in the direct energy deposition technology; it introduces the main processes, and analyzes the characteristics of tool-path problem. It explains the approaches applied in the literature to solve the problem; as these are mainly geometric approximations, they are far from optimal. Based on this analysis, this paper introduces a mathematical framework for direct energy deposition and a novel problem called sequence strategy generation. Finally, it solves the problem using a benchmark for several different parts. The results reveal that the approach can be applied to parts with different characteristics, and the solution to the sequence strategy problem can be used to generate tool-paths.